betweenness.centrality.clustering {RBGL}R Documentation

Graph clustering based on edge betweenness centrality

Description

Graph clustering based on edge betweenness centrality

Usage

betweenness.centrality.clustering(g, threshold = -1, normalize = T))

Arguments

g an instance of the graph class with edgemode “undirected”
threshold threshold to terminate clustering process
normalize boolean, when true, the threshold is compared with the normalized edge centrality based on the input graph; when false, the threshold is compared with the absolute edge centrality

Details

To implement graph clustering based on edge betweenness centrality. The algorithm is iterative, at each step it computes the edge betweenness centrality and removes the edge with the maximum betweenness centrality. See documentation on Clustering algorithms in Boost Graph Library for details.

Value

A list of

betweenness.centrality.vertices betweenness centrality of each vertex
betweenness.centrality.edges betweenness centrality of each edge
relative.betweenness.centrality.vertices relative betweenness centrality of each vertex
dominance central point dominance

Author(s)

Li Long <li.long@isb-sib.ch>

References

Boost Graph Library by Siek et al.

See Also

Examples

coex <- fromGXL(file(system.file("XML/conn.gxl",package="RBGL")))
coex@edgemode <- "undirected"
betweenness.centrality.clustering(coex)

[Package RBGL version 1.3.13 Index]